1
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Li SS, Xue CD, Li YJ, Chen XM, Zhao Y, Qin KR. Microfluidic characterization of single-cell biophysical properties and the applications in cancer diagnosis. Electrophoresis 2024; 45:1212-1232. [PMID: 37909658 DOI: 10.1002/elps.202300177] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2023] [Revised: 09/25/2023] [Accepted: 10/16/2023] [Indexed: 11/03/2023]
Abstract
Single-cell biophysical properties play a crucial role in regulating cellular physiological states and functions, demonstrating significant potential in the fields of life sciences and clinical diagnostics. Therefore, over the last few decades, researchers have developed various detection tools to explore the relationship between the biophysical changes of biological cells and human diseases. With the rapid advancement of modern microfabrication technology, microfluidic devices have quickly emerged as a promising platform for single-cell analysis offering advantages including high-throughput, exceptional precision, and ease of manipulation. Consequently, this paper provides an overview of the recent advances in microfluidic analysis and detection systems for single-cell biophysical properties and their applications in the field of cancer. The working principles and latest research progress of single-cell biophysical property detection are first analyzed, highlighting the significance of electrical and mechanical properties. The development of data acquisition and processing methods for real-time, high-throughput, and practical applications are then discussed. Furthermore, the differences in biophysical properties between tumor and normal cells are outlined, illustrating the potential for utilizing single-cell biophysical properties for tumor cell identification, classification, and drug response assessment. Lastly, we summarize the limitations of existing microfluidic analysis and detection systems in single-cell biophysical properties, while also pointing out the prospects and future directions of their applications in cancer diagnosis and treatment.
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Affiliation(s)
- Shan-Shan Li
- School of Mechanical Engineering, Dalian University of Technology, Dalian, Liaoning, P. R. China
| | - Chun-Dong Xue
- School of Biomedical Engineering, Faculty of Medicine, Dalian University of Technology, Dalian, Liaoning, P. R. China
| | - Yong-Jiang Li
- School of Biomedical Engineering, Faculty of Medicine, Dalian University of Technology, Dalian, Liaoning, P. R. China
| | - Xiao-Ming Chen
- School of Optoelectronic Engineering and Instrumentation Science, Dalian University of Technology, Dalian, Liaoning, P. R. China
| | - Yan Zhao
- Department of Stomach Surgery, Cancer Hospital of Dalian University of Technology, Liaoning Cancer Hospital and Institute, Shenyang, Liaoning, P. R. China
| | - Kai-Rong Qin
- School of Biomedical Engineering, Faculty of Medicine, Dalian University of Technology, Dalian, Liaoning, P. R. China
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2
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Zhu J, Pan S, Chai H, Zhao P, Feng Y, Cheng Z, Zhang S, Wang W. Microfluidic Impedance Cytometry Enabled One-Step Sample Preparation for Efficient Single-Cell Mass Spectrometry. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2024; 20:e2310700. [PMID: 38483007 DOI: 10.1002/smll.202310700] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Revised: 03/05/2024] [Indexed: 06/27/2024]
Abstract
Single-cell mass spectrometry (MS) is significant in biochemical analysis and holds great potential in biomedical applications. Efficient sample preparation like sorting (i.e., separating target cells from the mixed population) and desalting (i.e., moving the cells off non-volatile salt solution) is urgently required in single-cell MS. However, traditional sample preparation methods suffer from complicated operation with various apparatus, or insufficient performance. Herein, a one-step sample preparation strategy by leveraging label-free impedance flow cytometry (IFC) based microfluidics is proposed. Specifically, the IFC framework to characterize and sort single-cells is adopted. Simultaneously with sorting, the target cell is transferred from the local high-salinity buffer to the MS-compatible solution. In this way, one-step sorting and desalting are achieved and the collected cells can be directly fed for MS analysis. A high sorting efficiency (>99%), cancer cell purity (≈87%), and desalting efficiency (>99%), and the whole workflow of impedance-based separation and MS analysis of normal cells (MCF-10A) and cancer cells (MDA-MB-468) are verified. As a standalone sample preparation module, the microfluidic chip is compatible with a variety of MS analysis methods, and envisioned to provide a new paradigm in efficient MS sample preparation, and further in multi-modal (i.e., electrical and metabolic) characterization of single-cells.
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Affiliation(s)
- Junwen Zhu
- State Key Laboratory of Precision Measurement Technology and Instrument, Department of Precision Instrument, Tsinghua University, Beijing, 100084, China
| | - Siyuan Pan
- Department of Chemistry, Tsinghua University, Beijing, 100084, China
| | - Huichao Chai
- State Key Laboratory of Precision Measurement Technology and Instrument, Department of Precision Instrument, Tsinghua University, Beijing, 100084, China
| | - Peng Zhao
- State Key Laboratory of Precision Measurement Technology and Instrument, Department of Precision Instrument, Tsinghua University, Beijing, 100084, China
| | - Yongxiang Feng
- State Key Laboratory of Precision Measurement Technology and Instrument, Department of Precision Instrument, Tsinghua University, Beijing, 100084, China
| | - Zhen Cheng
- Department of Automation, Tsinghua University, Beijing, 100084, China
| | - Sichun Zhang
- Department of Chemistry, Tsinghua University, Beijing, 100084, China
| | - Wenhui Wang
- State Key Laboratory of Precision Measurement Technology and Instrument, Department of Precision Instrument, Tsinghua University, Beijing, 100084, China
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3
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Panklang N, Techaumnat B, Tanthanuch N, Chotivanich K, Horprathum M, Nakano M. On-Chip Impedance Spectroscopy of Malaria-Infected Red Blood Cells. SENSORS (BASEL, SWITZERLAND) 2024; 24:3186. [PMID: 38794040 PMCID: PMC11125259 DOI: 10.3390/s24103186] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/03/2024] [Revised: 04/30/2024] [Accepted: 05/10/2024] [Indexed: 05/26/2024]
Abstract
Malaria is a disease that affects millions of people worldwide, particularly in developing countries. The development of accurate and efficient methods for the detection of malaria-infected cells is crucial for effective disease management and control. This paper presents the electrical impedance spectroscopy (EIS) of normal and malaria-infected red blood cells. An EIS microfluidic device, comprising a microchannel and a pair of coplanar electrodes, was fabricated for single-cell measurements in a continuous manner. Based on the EIS results, the aim of this work is to discriminate Plasmodium falciparum-infected red blood cells from the normal ones. Different from typical impedance spectroscopy, our measurement was performed for the cells in a low-conductivity medium in a frequency range between 50 kHz and 800 kHz. Numerical simulation was utilized to study the suitability parameters of the microchannel and electrodes for the EIS experiment over the measurement frequencies. The measurement results have shown that by using the low-conductivity medium, we could focus on the change in the conductance caused by the presence of a cell in the sensing electrode gap. The results indicated a distinct frequency spectrum of the conductance between the normal and infected red blood cells, which can be further used for the detection of the disease.
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Affiliation(s)
- Nitipong Panklang
- Department of Electrical Engineering, Faculty of Engineering, Rajamangala University of Technology Thanyaburi, Pathum Thani 12110, Thailand;
| | - Boonchai Techaumnat
- Department of Electrical Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok 10330, Thailand
- Micro/Nano-Electro-Mechanical Integrated System Research Unit, Faculty of Engineering, Chulalongkorn University, Bangkok 10330, Thailand
| | - Nutthaphong Tanthanuch
- Department of Electrical and Computer Engineering, Faculty of Engineering, Thammasat School of Engineering, Thammasat University, Pathum Thani 12120, Thailand;
| | - Kesinee Chotivanich
- Cell and Tissue Culture Resources Unit, Department of Clinical Tropical Medicine, Faculty of Tropical Medicine, Mahidol University, Bangkok 10400, Thailand;
| | - Mati Horprathum
- Spectroscopic and Sensing Devices Research Group, NECTEC, NSTDA, Pathum Thani 12120, Thailand;
| | - Michihiko Nakano
- Faculty of Information Science and Electrical Engineering, Kyushu University, Fukuoka 819-0395, Japan;
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4
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Dahal N, Peak C, Ehrett C, Osterberg J, Cao M, Divan R, Wang P. Microwave Flow Cytometric Detection and Differentiation of Escherichia coli. SENSORS (BASEL, SWITZERLAND) 2024; 24:2870. [PMID: 38732977 PMCID: PMC11086155 DOI: 10.3390/s24092870] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/19/2024] [Revised: 04/24/2024] [Accepted: 04/26/2024] [Indexed: 05/13/2024]
Abstract
Label-free measurement and analysis of single bacterial cells are essential for food safety monitoring and microbial disease diagnosis. We report a microwave flow cytometric sensor with a microstrip sensing device with reduced channel height for bacterial cell measurement. Escherichia coli B and Escherichia coli K-12 were measured with the sensor at frequencies between 500 MHz and 8 GHz. The results show microwave properties of E. coli cells are frequency-dependent. A LightGBM model was developed to classify cell types at a high accuracy of 0.96 at 1 GHz. Thus, the sensor provides a promising label-free method to rapidly detect and differentiate bacterial cells. Nevertheless, the method needs to be further developed by comprehensively measuring different types of cells and demonstrating accurate cell classification with improved machine-learning techniques.
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Affiliation(s)
- Neelima Dahal
- Holcombe Department of Electrical and Computer Engineering, Clemson University, Clemson, SC 29634, USA; (N.D.); (J.O.)
| | - Caroline Peak
- Department of Bioengineering, Clemson University, Clemson, SC 29634, USA;
| | - Carl Ehrett
- Watt Family Innovation Center, Clemson University, Clemson, SC 29634, USA;
| | - Jeffrey Osterberg
- Holcombe Department of Electrical and Computer Engineering, Clemson University, Clemson, SC 29634, USA; (N.D.); (J.O.)
| | - Min Cao
- Department of Biological Sciences, Clemson University, Clemson, SC 29634, USA;
| | - Ralu Divan
- Argonne National Laboratory, Chicago, IL 60439, USA;
| | - Pingshan Wang
- Holcombe Department of Electrical and Computer Engineering, Clemson University, Clemson, SC 29634, USA; (N.D.); (J.O.)
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5
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Wang YK, Shi BW, Zhao JM, Wang YX, Jiang YF, Yang GL, Gao XD, Qiang T. Highly Sensitive and Linear Resonator-Based Biosensor for White Blood Cell Counting: Feasible Measurement Method and Intrinsic Mechanism Exploration. BIOSENSORS 2024; 14:180. [PMID: 38667173 PMCID: PMC11048127 DOI: 10.3390/bios14040180] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/11/2024] [Revised: 04/04/2024] [Accepted: 04/05/2024] [Indexed: 04/28/2024]
Abstract
Since different quantities of white blood cells (WBCs) in solution possess an adaptive osmotic pressure of cells, the WBCs themselves and in solution have similar concentrations, resulting in them having similar dielectric properties. Therefore, a microwave sensor could have difficulty in sensing the quantity variation when WBCs are in solution. This paper presents a highly sensitive, linear permittivity-inspired microwave biosensor for WBCs, counting through the evaporation method. Such a measurement method is proposed to record measurements after the cell solution is dripped onto the chip and is completely evaporated naturally. The proposed biosensor consists of an air-bridged asymmetric differential inductor and a centrally located circular fork-finger capacitor fabricated on a GaAs substrate using integrated passive fabrication technology. It is optimized to feature a larger sensitive area and improved Q-factor, which increases the effective area of interaction between cells and the electromagnetic field and facilitates the detection of their changes in number. The sensing relies on the dielectric properties of the cells and the change in the dielectric constant for different concentrations, and the change in resonance properties, which mainly represents the frequency shift, corresponds to the macroscopic change in the concentration of the cells. The microwave biosensors are used to measure biological samples with concentrations ranging from 0.25 × 106 to 8 × 106 cells per mL in a temperature (26.00 ± 0.40 °C) and humidity (54.40 ± 3.90 RH%) environment. The measurement results show a high sensitivity of 25.06 Hz/cells·mL-1 with a highly linear response of r2 = 0.99748. In addition, a mathematical modeling of individual cells in suspension is performed to estimate the dielectric constant of individual cells and further explain the working mechanism of the proposed microwave biosensor.
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Affiliation(s)
- Yi-Ke Wang
- School of Internet of Things Engineering, Institute of Advanced Technology, Jiangnan University, Wuxi 214122, China; (Y.-K.W.); (B.-W.S.); (J.-M.Z.); (Y.-X.W.); (Y.-F.J.)
| | - Bo-Wen Shi
- School of Internet of Things Engineering, Institute of Advanced Technology, Jiangnan University, Wuxi 214122, China; (Y.-K.W.); (B.-W.S.); (J.-M.Z.); (Y.-X.W.); (Y.-F.J.)
| | - Jun-Ming Zhao
- School of Internet of Things Engineering, Institute of Advanced Technology, Jiangnan University, Wuxi 214122, China; (Y.-K.W.); (B.-W.S.); (J.-M.Z.); (Y.-X.W.); (Y.-F.J.)
| | - Yan-Xiong Wang
- School of Internet of Things Engineering, Institute of Advanced Technology, Jiangnan University, Wuxi 214122, China; (Y.-K.W.); (B.-W.S.); (J.-M.Z.); (Y.-X.W.); (Y.-F.J.)
| | - Yan-Feng Jiang
- School of Internet of Things Engineering, Institute of Advanced Technology, Jiangnan University, Wuxi 214122, China; (Y.-K.W.); (B.-W.S.); (J.-M.Z.); (Y.-X.W.); (Y.-F.J.)
| | - Gang-Long Yang
- State Key Laboratory of Biochemical Engineering, Institute of Process Engineering, Chinese Academy of Sciences, Beijing 100190, China;
- Key Laboratory of Biopharmaceutical Preparation and Delivery, Chinese Academy of Sciences, Beijing 100190, China
| | - Xiao-Dong Gao
- School of Biotechnology, The Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, Jiangnan University, Wuxi 214122, China
| | - Tian Qiang
- School of Internet of Things Engineering, Institute of Advanced Technology, Jiangnan University, Wuxi 214122, China; (Y.-K.W.); (B.-W.S.); (J.-M.Z.); (Y.-X.W.); (Y.-F.J.)
- School of Biotechnology, The Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, Jiangnan University, Wuxi 214122, China
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6
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Zhang S, Han Z, Qi H, Liu S, Liu B, Sun C, Feng Z, Sun M, Duan X. Convolutional Neural Network-Driven Impedance Flow Cytometry for Accurate Bacterial Differentiation. Anal Chem 2024; 96:4419-4429. [PMID: 38448396 DOI: 10.1021/acs.analchem.3c04421] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/08/2024]
Abstract
Impedance flow cytometry (IFC) has been demonstrated to be an efficient tool for label-free bacterial investigation to obtain the electrical properties in real time. However, the accurate differentiation of different species of bacteria by IFC technology remains a challenge owing to the insignificant differences in data. Here, we developed a convolutional neural networks (ConvNet) deep learning approach to enhance the accuracy and efficiency of the IFC toward distinguishing various species of bacteria. First, more than 1 million sets of impedance data (comprising 42 characteristic features for each set) of various groups of bacteria were trained by the ConvNet model. To improve the efficiency for data analysis, the Spearman correlation coefficient and the mean decrease accuracy of the random forest algorithm were introduced to eliminate feature interaction and extract the opacity of impedance related to the bacterial wall and membrane structure as the predominant features in bacterial differentiation. Moreover, the 25 optimized features were selected with differentiation accuracies of >96% for three groups of bacteria (bacilli, cocci, and vibrio) and >95% for two species of bacilli (Escherichia coli and Salmonella enteritidis), compared to machine learning algorithms (complex tree, linear discriminant, and K-nearest neighbor algorithms) with a maximum accuracy of 76.4%. Furthermore, bacterial differentiation was achieved on spiked samples of different species with different mixing ratios. The proposed ConvNet deep learning-assisted data analysis method of IFC exhibits advantages in analyzing a huge number of data sets with capacity for extracting predominant features within multicomponent information and will bring about progress and advances in the fields of both biosensing and data analysis.
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Affiliation(s)
- Shuaihua Zhang
- State Key Laboratory of Precision Measuring Technology & Instruments, College of Precision Instrument and Optoelectronics Engineering, Tianjin University, Tianjin 300072, China
| | - Ziyu Han
- State Key Laboratory of Precision Measuring Technology & Instruments, College of Precision Instrument and Optoelectronics Engineering, Tianjin University, Tianjin 300072, China
| | - Hang Qi
- State Key Laboratory of Precision Measuring Technology & Instruments, College of Precision Instrument and Optoelectronics Engineering, Tianjin University, Tianjin 300072, China
| | - Siyuan Liu
- State Key Laboratory of Precision Measuring Technology & Instruments, College of Precision Instrument and Optoelectronics Engineering, Tianjin University, Tianjin 300072, China
| | - Bohua Liu
- State Key Laboratory of Precision Measuring Technology & Instruments, College of Precision Instrument and Optoelectronics Engineering, Tianjin University, Tianjin 300072, China
| | - Chongling Sun
- State Key Laboratory of Precision Measuring Technology & Instruments, College of Precision Instrument and Optoelectronics Engineering, Tianjin University, Tianjin 300072, China
| | - Zhe Feng
- Wuqing District Center for Disease Control and Prevention, Tianjin 301700, China
| | - Meiqing Sun
- Wuqing District Center for Disease Control and Prevention, Tianjin 301700, China
| | - Xuexin Duan
- State Key Laboratory of Precision Measuring Technology & Instruments, College of Precision Instrument and Optoelectronics Engineering, Tianjin University, Tianjin 300072, China
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7
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Chen J, Zhong J, Lei H, Ai Y. Label-free multidimensional bacterial characterization with an ultrawide detectable concentration range by microfluidic impedance cytometry. LAB ON A CHIP 2023; 23:5029-5038. [PMID: 37909182 DOI: 10.1039/d3lc00799e] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/02/2023]
Abstract
Rapid and accurate identification of bacteria is of great importance to public health in various fields, including medical diagnostics, food safety, and environmental monitoring. However, most existing bacterial detection methods have very narrow detectable concentration ranges and limited detection information, which easily leads to wrong diagnosis and treatment. This work presents a novel high-throughput microfluidic electrical impedance-based multidimensional single-bacterium profiling system for ultrawide concentration range detection and accurate differentiation of viability and Gram types of bacteria. The electrical impedance-based microfluidic cytometry is capable of multi-frequency impedance quantification, which allows profiling of the bacteria size, concentration, and membrane impedance as an indicator of bacterial viability and Gram properties in a single flow-through interrogation. It has been demonstrated that this novel impedance cytometry has an ultrawide bacterial counting range (102-108 cells per mL), and exhibits a rapid and accurate discrimination of viability and Gram types of bacteria in a label-free manner. Escherichia coli (E. coli) has been used as an analog species for the accuracy assessment of the electrical impedance-based bacterial detection system in an authentic complex beverage matrix within 24 hours. The impedance-based quantifications of viable bacteria are consistent with those obtained by the classical bacterial colony counting method (R2 = 0.996). This work could pave the way for providing a novel microfluidic cytometry system for rapid and multidimensional bacterial detection in diverse areas.
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Affiliation(s)
- Jiahong Chen
- Guangdong Provincial Key Laboratory of Food Quality and Safety/National-Local Joint Engineering Research Center for Machining and Safety of Livestock and Poultry Products, College of Food Science, South China Agricultural University, Guangzhou 510642, China.
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou 510642, China
| | - Jianwei Zhong
- Pillar of Engineering Product Development, Singapore University of Technology and Design, 8 Somapah Road, Singapore 487372, Singapore.
| | - Hongtao Lei
- Guangdong Provincial Key Laboratory of Food Quality and Safety/National-Local Joint Engineering Research Center for Machining and Safety of Livestock and Poultry Products, College of Food Science, South China Agricultural University, Guangzhou 510642, China.
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou 510642, China
| | - Ye Ai
- Pillar of Engineering Product Development, Singapore University of Technology and Design, 8 Somapah Road, Singapore 487372, Singapore.
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8
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Torres-Castro K, Acuña-Umaña K, Lesser-Rojas L, Reyes DR. Microfluidic Blood Separation: Key Technologies and Critical Figures of Merit. MICROMACHINES 2023; 14:2117. [PMID: 38004974 PMCID: PMC10672873 DOI: 10.3390/mi14112117] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/05/2023] [Revised: 11/01/2023] [Accepted: 11/10/2023] [Indexed: 11/26/2023]
Abstract
Blood is a complex sample comprised mostly of plasma, red blood cells (RBCs), and other cells whose concentrations correlate to physiological or pathological health conditions. There are also many blood-circulating biomarkers, such as circulating tumor cells (CTCs) and various pathogens, that can be used as measurands to diagnose certain diseases. Microfluidic devices are attractive analytical tools for separating blood components in point-of-care (POC) applications. These platforms have the potential advantage of, among other features, being compact and portable. These features can eventually be exploited in clinics and rapid tests performed in households and low-income scenarios. Microfluidic systems have the added benefit of only needing small volumes of blood drawn from patients (from nanoliters to milliliters) while integrating (within the devices) the steps required before detecting analytes. Hence, these systems will reduce the associated costs of purifying blood components of interest (e.g., specific groups of cells or blood biomarkers) for studying and quantifying collected blood fractions. The microfluidic blood separation field has grown since the 2000s, and important advances have been reported in the last few years. Nonetheless, real POC microfluidic blood separation platforms are still elusive. A widespread consensus on what key figures of merit should be reported to assess the quality and yield of these platforms has not been achieved. Knowing what parameters should be reported for microfluidic blood separations will help achieve that consensus and establish a clear road map to promote further commercialization of these devices and attain real POC applications. This review provides an overview of the separation techniques currently used to separate blood components for higher throughput separations (number of cells or particles per minute). We present a summary of the critical parameters that should be considered when designing such devices and the figures of merit that should be explicitly reported when presenting a device's separation capabilities. Ultimately, reporting the relevant figures of merit will benefit this growing community and help pave the road toward commercialization of these microfluidic systems.
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Affiliation(s)
- Karina Torres-Castro
- Biophysical and Biomedical Measurements Group, National Institute of Standards and Technology (NIST), 100 Bureau Drive, Gaithersburg, MD 20899, USA;
- Theiss Research, La Jolla, CA 92037, USA
| | - Katherine Acuña-Umaña
- Medical Devices Master’s Program, Instituto Tecnológico de Costa Rica (ITCR), Cartago 30101, Costa Rica
| | - Leonardo Lesser-Rojas
- Research Center in Atomic, Nuclear and Molecular Sciences (CICANUM), San José 11501, Costa Rica;
- School of Physics, Universidad de Costa Rica (UCR), San José 11501, Costa Rica
| | - Darwin R. Reyes
- Biophysical and Biomedical Measurements Group, National Institute of Standards and Technology (NIST), 100 Bureau Drive, Gaithersburg, MD 20899, USA;
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Moore JH, Salahi A, Honrado C, Warburton C, Tate S, Warren CA, Swami NS. Correlating Antibiotic-Induced Dysbiosis to Clostridioides difficile Spore Germination and Host Susceptibility to Infection Using an Ex Vivo Assay. ACS Infect Dis 2023; 9:1878-1888. [PMID: 37756389 PMCID: PMC10581205 DOI: 10.1021/acsinfecdis.3c00192] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Indexed: 09/29/2023]
Abstract
Antibiotic-induced microbiota disruption and its persistence create conditions for dysbiosis and colonization by opportunistic pathogens, such as those causing Clostridioides difficile (C. difficile) infection (CDI), which is the most severe hospital-acquired intestinal infection. Given the wide differences in microbiota across hosts and in their recovery after antibiotic treatments, there is a need for assays to assess the influence of dysbiosis and its recovery dynamics on the susceptibility of the host to CDI. Germination of C. difficile spores is a key virulence trait for the onset of CDI, which is influenced by the level of primary vs secondary bile acids in the intestinal milieu that is regulated by the microbiota composition. Herein, the germination of C. difficile spores in fecal supernatant from mice that are subject to varying degrees of antibiotic treatment is utilized as an ex vivo assay to predict intestinal dysbiosis in the host based on their susceptibility to CDI, as determined by in vivo CDI metrics in the same mouse model. Quantification of spore germination down to lower detection limits than the colony-forming assay is achieved by using impedance cytometry to count single vegetative bacteria that are identified based on their characteristic electrical physiology for distinction vs aggregated spores and cell debris in the media. As a result, germination can be quantified at earlier time points and with fewer spores for correlation to CDI outcomes. This sets the groundwork for a point-of-care tool to gauge the susceptibility of human microbiota to CDI after antibiotic treatments.
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Affiliation(s)
- John H. Moore
- Electrical
and Computer Engineering, University of
Virginia, Charlottesville, Virginia 22904, United States
| | - Armita Salahi
- Electrical
and Computer Engineering, University of
Virginia, Charlottesville, Virginia 22904, United States
| | - Carlos Honrado
- Electrical
and Computer Engineering, University of
Virginia, Charlottesville, Virginia 22904, United States
| | - Christopher Warburton
- Electrical
and Computer Engineering, University of
Virginia, Charlottesville, Virginia 22904, United States
| | - Steven Tate
- Electrical
and Computer Engineering, University of
Virginia, Charlottesville, Virginia 22904, United States
| | - Cirle A. Warren
- Infectious
Diseases, School of Medicine, University
of Virginia, Charlottesville, Virginia 22903, United States
| | - Nathan S. Swami
- Electrical
and Computer Engineering, University of
Virginia, Charlottesville, Virginia 22904, United States
- Chemistry, University
of Virginia, Charlottesville, Virginia 22904, United States
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10
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Tang T, Julian T, Ma D, Yang Y, Li M, Hosokawa Y, Yalikun Y. A review on intelligent impedance cytometry systems: Development, applications and advances. Anal Chim Acta 2023; 1269:341424. [PMID: 37290859 DOI: 10.1016/j.aca.2023.341424] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Revised: 05/22/2023] [Accepted: 05/23/2023] [Indexed: 06/10/2023]
Abstract
Impedance cytometry is a well-established technique for counting and analyzing single cells, with several advantages, such as convenience, high throughput, and no labeling required. A typical experiment consists of the following steps: single-cell measurement, signal processing, data calibration, and particle subtype identification. At the beginning of this article, we compared commercial and self-developed options extensively and provided references for developing reliable detection systems, which are necessary for cell measurement. Then, a number of typical impedance metrics and their relationships to biophysical properties of cells were analyzed with respect to the impedance signal analysis. Given the rapid advances of intelligent impedance cytometry in the past decade, this article also discussed the development of representative machine learning-based approaches and systems, and their applications in data calibration and particle identification. Finally, the remaining challenges facing the field were summarized, and potential future directions for each step of impedance detection were discussed.
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Affiliation(s)
- Tao Tang
- Division of Materials Science, Nara Institute of Science and Technology, 8916-5 Takayamacho, Ikoma, Nara, 630-0192, Japan; Department of Biomedical Engineering, National University of Singapore, 4 Engineering Drive 3, Singapore, 117583, Singapore
| | - Trisna Julian
- Division of Materials Science, Nara Institute of Science and Technology, 8916-5 Takayamacho, Ikoma, Nara, 630-0192, Japan
| | - Doudou Ma
- Center for Biosystems Dynamics Research (BDR), RIKEN, 1-3 Yamadaoka, Suita, Osaka, 565-0871, Japan
| | - Yang Yang
- Institute of Deep-Sea Science and Engineering, Chinese Academy of Sciences, Sanya, Hainan, 572000, PR China
| | - Ming Li
- School of Engineering, Macquarie University, Sydney, 2109, Australia
| | - Yoichiroh Hosokawa
- Division of Materials Science, Nara Institute of Science and Technology, 8916-5 Takayamacho, Ikoma, Nara, 630-0192, Japan
| | - Yaxiaer Yalikun
- Division of Materials Science, Nara Institute of Science and Technology, 8916-5 Takayamacho, Ikoma, Nara, 630-0192, Japan; Center for Biosystems Dynamics Research (BDR), RIKEN, 1-3 Yamadaoka, Suita, Osaka, 565-0871, Japan.
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11
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Troiano C, De Ninno A, Casciaro B, Riccitelli F, Park Y, Businaro L, Massoud R, Mangoni ML, Bisegna P, Stella L, Caselli F. Rapid Assessment of Susceptibility of Bacteria and Erythrocytes to Antimicrobial Peptides by Single-Cell Impedance Cytometry. ACS Sens 2023. [PMID: 37421371 PMCID: PMC10391704 DOI: 10.1021/acssensors.3c00256] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/10/2023]
Abstract
Antimicrobial peptides (AMPs) represent a promising class of compounds to fight antibiotic-resistant infections. In most cases, they kill bacteria by making their membrane permeable and therefore exhibit low propensity to induce bacterial resistance. In addition, they are often selective, killing bacteria at concentrations lower than those at which they are toxic to the host. However, clinical applications of AMPs are hindered by a limited understanding of their interactions with bacteria and human cells. Standard susceptibility testing methods are based on the analysis of the growth of a bacterial population and therefore require several hours. Moreover, different assays are required to assess the toxicity to host cells. In this work, we propose the use of microfluidic impedance cytometry to explore the action of AMPs on both bacteria and host cells in a rapid manner and with single-cell resolution. Impedance measurements are particularly well-suited to detect the effects of AMPs on bacteria, due to the fact that the mechanism of action involves perturbation of the permeability of cell membranes. We show that the electrical signatures of Bacillus megaterium cells and human red blood cells (RBCs) reflect the action of a representative antimicrobial peptide, DNS-PMAP23. In particular, the impedance phase at high frequency (e.g., 11 or 20 MHz) is a reliable label-free metric for monitoring DNS-PMAP23 bactericidal activity and toxicity to RBCs. The impedance-based characterization is validated by comparison with standard antibacterial activity assays and absorbance-based hemolytic activity assays. Furthermore, we demonstrate the applicability of the technique to a mixed sample of B. megaterium cells and RBCs, which paves the way to study AMP selectivity for bacterial versus eukaryotic cells in the presence of both cell types.
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Affiliation(s)
- Cassandra Troiano
- Department of Chemical Science and Technologies, University of Rome Tor Vergata, 00133 Rome, Italy
| | - Adele De Ninno
- Institute for Photonics and Nanotechnologies, Italian National Research Council, 00133 Rome, Italy
| | - Bruno Casciaro
- Laboratory affiliated to Pasteur Italia-Fondazione Cenci Bolognetti, Department of Biochemical Sciences "A. Rossi Fanelli", Sapienza University of Rome, 00185 Rome, Italy
| | - Francesco Riccitelli
- Department of Chemical Science and Technologies, University of Rome Tor Vergata, 00133 Rome, Italy
| | - Yoonkyung Park
- Department of Biomedical Science, College of Natural science, Chosun University, Gwangju 61452, Republic of Korea
| | - Luca Businaro
- Institute for Photonics and Nanotechnologies, Italian National Research Council, 00133 Rome, Italy
| | - Renato Massoud
- Department of Experimental Medicine, University of Rome Tor Vergata, 00133 Rome, Italy
| | - Maria Luisa Mangoni
- Laboratory affiliated to Pasteur Italia-Fondazione Cenci Bolognetti, Department of Biochemical Sciences "A. Rossi Fanelli", Sapienza University of Rome, 00185 Rome, Italy
| | - Paolo Bisegna
- Department of Civil Engineering and Computer Science, University of Rome Tor Vergata, 00133 Rome, Italy
| | - Lorenzo Stella
- Department of Chemical Science and Technologies, University of Rome Tor Vergata, 00133 Rome, Italy
| | - Federica Caselli
- Department of Civil Engineering and Computer Science, University of Rome Tor Vergata, 00133 Rome, Italy
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12
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Salahi A, Honrado C, Moore J, Adair S, Bauer TW, Swami NS. Supervised learning on impedance cytometry data for label-free biophysical distinction of pancreatic cancer cells versus their associated fibroblasts under gemcitabine treatment. Biosens Bioelectron 2023; 231:115262. [PMID: 37058962 PMCID: PMC10134450 DOI: 10.1016/j.bios.2023.115262] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2022] [Revised: 02/14/2023] [Accepted: 03/23/2023] [Indexed: 04/03/2023]
Abstract
Chemotherapy failure in pancreatic cancer patients is widely attributed to cancer cell reprogramming towards drug resistance by cancer associated fibroblasts (CAFs), which are the abundant cell type in the tumor microenvironment. Association of drug resistance to specific cancer cell phenotypes within multicellular tumors can advance isolation protocols for enabling cell-type specific gene expression markers to identify drug resistance. This requires the distinction of drug resistant cancer cells versus CAFs, which is challenging since permeabilization of CAF cells during drug treatment can cause non-specific uptake of cancer cell-specific stains. Cellular biophysical metrics, on the other hand, can provide multiparametric information to assess the gradual alteration of target cancer cells towards drug resistance, but these phenotypes need to be distinguished versus CAFs. Using pancreatic cancer cells and CAFs from a metastatic patient-derived tumor that exhibits cancer cell drug resistance under CAF co-culture, the biophysical metrics from multifrequency single-cell impedance cytometry are utilized for distinction of the subpopulation of viable cancer cells versus CAFs, before and after gemcitabine treatment. This is accomplished through supervised machine learning after training the model using key impedance metrics for cancer cells and CAFs from transwell co-cultures, so that an optimized classifier model can recognize each cell type and predict their respective proportions in multicellular tumor samples, before and after gemcitabine treatment, as validated by their confusion matrix and flow cytometry assays. In this manner, an aggregate of the distinguishing biophysical metrics of viable cancer cells after gemcitabine treatment in co-cultures with CAFs can be used in longitudinal studies, to classify and isolate the drug resistant subpopulation for identifying markers.
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Affiliation(s)
- Armita Salahi
- Electrical & Computer Engineering, University of Virginia, Charlottesville, VA, 22904, USA
| | - Carlos Honrado
- Electrical & Computer Engineering, University of Virginia, Charlottesville, VA, 22904, USA.
| | - John Moore
- Electrical & Computer Engineering, University of Virginia, Charlottesville, VA, 22904, USA
| | - Sara Adair
- Surgery, School of Medicine, University of Virginia, Charlottesville, USA
| | - Todd W Bauer
- Surgery, School of Medicine, University of Virginia, Charlottesville, USA
| | - Nathan S Swami
- Electrical & Computer Engineering, University of Virginia, Charlottesville, VA, 22904, USA; Chemistry, University of Virginia, Charlottesville, USA.
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13
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Zhu J, Feng Y, Chai H, Liang F, Cheng Z, Wang W. Performance-enhanced clogging-free viscous sheath constriction impedance flow cytometry. LAB ON A CHIP 2023; 23:2531-2539. [PMID: 37082895 DOI: 10.1039/d3lc00178d] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
As a label-free and high-throughput single cell analysis platform, impedance flow cytometry (IFC) suffers from clogging caused by a narrow microchannel as mechanical constriction (MC). Current sheath constriction (SC) solutions lack systematic evaluation of the performance and proper guidelines for the sheath fluid. Herein, we hypothesize that the viscosity of the non-conductive liquid is the key to the performance of SC, and propose to employ non-conductive viscous sheath flow in SC to unlock the tradeoff between sensitivity and throughput, while ensuring measurement accuracy. By placing MC and SC in series in the same microfluidic chip, we established an evaluation platform to prove the hypothesis. Through modeling analysis and experiments, we confirmed the accuracy (error < 1.60% ± 4.71%) of SC w.r.t. MC, and demonstrated that viscous non-conductive PEG solution achieved an improved sensitivity (7.92×) and signal-to-noise ratio (1.42×) in impedance measurement, with the accuracy maintained and free of clogging. Viscous SC IFC also shows satisfactory ability to distinguish different types of cancer cells and different subtypes of human breast cancer cells. It is envisioned that viscous SC IFC paves the way for IFC to be really usable in practice with clogging-free, accurate, and sensitive performance.
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Affiliation(s)
- Junwen Zhu
- State Key Laboratory of Precision Measurement Technology and Instrument, Department of Precision Instrument, Tsinghua University, Beijing, P. R. China.
| | - Yongxiang Feng
- State Key Laboratory of Precision Measurement Technology and Instrument, Department of Precision Instrument, Tsinghua University, Beijing, P. R. China.
| | - Huichao Chai
- State Key Laboratory of Precision Measurement Technology and Instrument, Department of Precision Instrument, Tsinghua University, Beijing, P. R. China.
| | - Fei Liang
- State Key Laboratory of Precision Measurement Technology and Instrument, Department of Precision Instrument, Tsinghua University, Beijing, P. R. China.
| | - Zhen Cheng
- Department of Automation, Tsinghua University, Beijing, P. R. China
| | - Wenhui Wang
- State Key Laboratory of Precision Measurement Technology and Instrument, Department of Precision Instrument, Tsinghua University, Beijing, P. R. China.
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14
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de Bruijn DS, Van de Waal DB, Helmsing NR, Olthuis W, van den Berg A. Microfluidic Impedance Cytometry for Single-Cell Particulate Inorganic Carbon:Particulate Organic Carbon Measurements of Calcifying Algae. GLOBAL CHALLENGES (HOBOKEN, NJ) 2023; 7:2200151. [PMID: 36910468 PMCID: PMC10000273 DOI: 10.1002/gch2.202200151] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Revised: 11/16/2022] [Indexed: 06/18/2023]
Abstract
Calcifying algae, like coccolithophores, greatly contribute to the oceanic carbon cycle and are therefore of particular interest for ocean carbon models. They play a key role in two processes that are important for the effective CO2 flux: The organic carbon pump (photosynthesis) and the inorganic carbon pump (calcification). The relative contribution of calcification and photosynthesis can be measured in algae by the amount of particulate inorganic carbon (PIC) and particulate organic carbon (POC). A microfluidic impedance cytometer is presented, enabling non-invasive and high-throughput assessment of the calcification state of single coccolithophore cells. Gradual modification of the exoskeleton by acidification results in a strong linear fit (R 2 = 0.98) between the average electrical phase and the PIC:POC ratio of the coccolithophore Emiliania huxleyi 920/9. The effect of different CO2 treatments on the PIC:POC ratio, however, is inconclusive, indicating that there is no strong effect observed for this particular strain. Lower PIC:POC ratios in cultures that grew to higher cell densities are found, which are also recorded with the impedance-based PIC:POC sensor. The development of this new quantification tool for small volumes paves the way for high-throughput analysis while applying multi-variable environmental stressors to support projections of the future marine carbon cycle.
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Affiliation(s)
- Douwe S. de Bruijn
- BIOS Lab‐on‐a‐Chip groupMESA+ Institute for NanotechnologyMax Planck—University of Twente Center for Complex Fluid DynamicsUniversity of TwenteDrienerlolaan 5EnschedeOverijssel7522 NBThe Netherlands
| | - Dedmer B. Van de Waal
- Department of Aquatic EcologyNetherlands Institute of Ecology (NIOO‐KNAW)Droevendaalsesteeg 10Wageningen6708 PBThe Netherlands
| | - Nico R. Helmsing
- Department of Aquatic EcologyNetherlands Institute of Ecology (NIOO‐KNAW)Droevendaalsesteeg 10Wageningen6708 PBThe Netherlands
| | - Wouter Olthuis
- BIOS Lab‐on‐a‐Chip groupMESA+ Institute for NanotechnologyMax Planck—University of Twente Center for Complex Fluid DynamicsUniversity of TwenteDrienerlolaan 5EnschedeOverijssel7522 NBThe Netherlands
| | - Albert van den Berg
- BIOS Lab‐on‐a‐Chip groupMESA+ Institute for NanotechnologyMax Planck—University of Twente Center for Complex Fluid DynamicsUniversity of TwenteDrienerlolaan 5EnschedeOverijssel7522 NBThe Netherlands
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15
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Ferguson CA, Hwang JCM, Zhang Y, Cheng X. Single-Cell Classification Based on Population Nucleus Size Combining Microwave Impedance Spectroscopy and Machine Learning. SENSORS (BASEL, SWITZERLAND) 2023; 23:1001. [PMID: 36679798 PMCID: PMC9860723 DOI: 10.3390/s23021001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Revised: 01/04/2023] [Accepted: 01/13/2023] [Indexed: 06/17/2023]
Abstract
Many recent efforts in the diagnostic field address the accessibility of cancer diagnosis. Typical histological staining methods identify cancer cells visually by a larger nucleus with more condensed chromatin. Machine learning (ML) has been incorporated into image analysis for improving this process. Recently, impedance spectrometers have been shown to generate all-inclusive lab-on-a-chip platforms to detect nucleus abnormities. In this paper, a wideband electrical sensor and data analysis paradigm that can identify nuclear changes shows the realization of a single-cell microfluidic device to detect nuclei of altered sizes. To model cells of altered nucleus, Jurkat cells were treated to enlarge or shrink their nucleus followed by broadband sensing to obtain the S-parameters of single cells. The ability to deduce important frequencies associated with nucleus size is demonstrated and used to improve classification models in both binary and multiclass scenarios, despite a heterogeneous and overlapping cell population. The important frequency features match those predicted in a double-shell circuit model published in prior work, demonstrating a coherent new analytical technique for electrical data analysis. The electrical sensing platform assisted by ML with impressive accuracy of cell classification looks forward to a label-free and flexible approach to cancer diagnosis.
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Affiliation(s)
| | - James C. M. Hwang
- Department of Materials Science and Engineering, Cornell University, Ithaca, NY 14853, USA
| | - Yu Zhang
- Department of Bioengineering, Lehigh University, Bethlehem, PA 18015, USA
| | - Xuanhong Cheng
- Department of Bioengineering, Lehigh University, Bethlehem, PA 18015, USA
- Department of Materials Science and Engineering, Lehigh University, Bethlehem, PA 18015, USA
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16
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Grigorev GV, Lebedev AV, Wang X, Qian X, Maksimov GV, Lin L. Advances in Microfluidics for Single Red Blood Cell Analysis. BIOSENSORS 2023; 13:117. [PMID: 36671952 PMCID: PMC9856164 DOI: 10.3390/bios13010117] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 12/04/2022] [Accepted: 12/23/2022] [Indexed: 05/24/2023]
Abstract
The utilizations of microfluidic chips for single RBC (red blood cell) studies have attracted great interests in recent years to filter, trap, analyze, and release single erythrocytes for various applications. Researchers in this field have highlighted the vast potential in developing micro devices for industrial and academia usages, including lab-on-a-chip and organ-on-a-chip systems. This article critically reviews the current state-of-the-art and recent advances of microfluidics for single RBC analyses, including integrated sensors and microfluidic platforms for microscopic/tomographic/spectroscopic single RBC analyses, trapping arrays (including bifurcating channels), dielectrophoretic and agglutination/aggregation studies, as well as clinical implications covering cancer, sepsis, prenatal, and Sickle Cell diseases. Microfluidics based RBC microarrays, sorting/counting and trapping techniques (including acoustic, dielectrophoretic, hydrodynamic, magnetic, and optical techniques) are also reviewed. Lastly, organs on chips, multi-organ chips, and drug discovery involving single RBC are described. The limitations and drawbacks of each technology are addressed and future prospects are discussed.
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Affiliation(s)
- Georgii V. Grigorev
- Data Science and Information Technology Research Center, Tsinghua Berkeley Shenzhen Institute, Tsinghua University, Shenzhen 518055, China
- Mechanical Engineering Department, University of California in Berkeley, Berkeley, CA 94720, USA
- School of Information Technology, Cherepovets State University, 162600 Cherepovets, Russia
| | - Alexander V. Lebedev
- Machine Building Department, Bauman Moscow State University, 105005 Moscow, Russia
| | - Xiaohao Wang
- Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China
| | - Xiang Qian
- Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China
| | - George V. Maksimov
- Faculty of Biology, Lomonosov Moscow State University, 119991 Moscow, Russia
- Physical metallurgy Department, Federal State Autonomous Educational Institution of Higher Education National Research Technological University “MISiS”, 119049 Moscow, Russia
| | - Liwei Lin
- Mechanical Engineering Department, University of California in Berkeley, Berkeley, CA 94720, USA
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17
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McCorry MC, Reardon KF, Black M, Williams C, Babakhanova G, Halpern JM, Sarkar S, Swami NS, Mirica KA, Boermeester S, Underhill A. Sensor technologies for quality control in engineered tissue manufacturing. Biofabrication 2022; 15:10.1088/1758-5090/ac94a1. [PMID: 36150372 PMCID: PMC10283157 DOI: 10.1088/1758-5090/ac94a1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Accepted: 09/23/2022] [Indexed: 11/11/2022]
Abstract
The use of engineered cells, tissues, and organs has the opportunity to change the way injuries and diseases are treated. Commercialization of these groundbreaking technologies has been limited in part by the complex and costly nature of their manufacture. Process-related variability and even small changes in the manufacturing process of a living product will impact its quality. Without real-time integrated detection, the magnitude and mechanism of that impact are largely unknown. Real-time and non-destructive sensor technologies are key for in-process insight and ensuring a consistent product throughout commercial scale-up and/or scale-out. The application of a measurement technology into a manufacturing process requires cell and tissue developers to understand the best way to apply a sensor to their process, and for sensor manufacturers to understand the design requirements and end-user needs. Furthermore, sensors to monitor component cells' health and phenotype need to be compatible with novel integrated and automated manufacturing equipment. This review summarizes commercially relevant sensor technologies that can detect meaningful quality attributes during the manufacturing of regenerative medicine products, the gaps within each technology, and sensor considerations for manufacturing.
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Affiliation(s)
- Mary Clare McCorry
- Advanced Regenerative Manufacturing Institute, Manchester, NH 03101, United States of America
| | - Kenneth F Reardon
- Chemical and Biological Engineering and Biomedical Engineering, Colorado State University, Fort Collins, CO 80521, United States of America
| | - Marcie Black
- Advanced Silicon Group, Lowell, MA 01854, United States of America
| | - Chrysanthi Williams
- Access Biomedical Solutions, Trinity, Florida 34655, United States of America
| | - Greta Babakhanova
- National Institute of Standards and Technology, Gaithersburg, MD 20899, United States of America
| | - Jeffrey M Halpern
- Department of Chemical Engineering, University of New Hampshire, Durham, NH 03824, United States of America
- Materials Science and Engineering Program, University of New Hampshire, Durham, NH 03824, United States of America
| | - Sumona Sarkar
- National Institute of Standards and Technology, Gaithersburg, MD 20899, United States of America
| | - Nathan S Swami
- Electrical and Computer Engineering, University of Virginia, Charlottesville, VA 22904, United States of America
| | - Katherine A Mirica
- Department of Chemistry, Dartmouth College, Hanover, NH 03755, United States of America
| | - Sarah Boermeester
- Advanced Regenerative Manufacturing Institute, Manchester, NH 03101, United States of America
| | - Abbie Underhill
- Scientific Bioprocessing Inc., Pittsburgh, PA 15238, United States of America
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18
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Single-cell assessment of the modulation of macrophage activation by ex vivo intervertebral discs using impedance cytometry. Biosens Bioelectron 2022; 210:114346. [PMID: 35569268 PMCID: PMC9623412 DOI: 10.1016/j.bios.2022.114346] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2022] [Revised: 04/30/2022] [Accepted: 05/04/2022] [Indexed: 11/21/2022]
Abstract
Measurement of macrophage activation and its modulation for immune regulation is of great interest to arrest inflammatory responses associated with degeneration of intervertebral discs that cause chronic back pain, and with transplants that face immune rejection. Due to the phenotypic plasticity of macrophages that serve multiple immune functions, the net disease outcome is determined by a balance of subpopulations with competing functions, highlighting the need for single-cell methods to quantify heterogeneity in their activation phenotypes. However, since macrophage activation can follow several signaling pathways, cytometry after fluorescent staining of markers with antibodies does not often provide dose-dependent information on activation dynamics. We present high throughput single-cell impedance cytometry for multiparametric measurement of biophysical changes to individual macrophages for quantifying activation in a dose and duration dependent manner, without relying on a particular signaling pathway. Impedance phase metrics measured at two frequencies and the electrical diameter from impedance magnitude at lower frequencies are used in tandem to benchmark macrophage activation by degenerated discs against that from lipopolysaccharide stimulation at varying dose and duration levels, so that reversal of the activation state by curcumin can be ascertained. This label-free single-cell measurement method can form the basis for platforms to screen therapies for inflammation, thereby addressing the chronic problem of back pain.
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19
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Caselli F, Reale R, De Ninno A, Spencer D, Morgan H, Bisegna P. Deciphering impedance cytometry signals with neural networks. LAB ON A CHIP 2022; 22:1714-1722. [PMID: 35353108 DOI: 10.1039/d2lc00028h] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/10/2023]
Abstract
Microfluidic impedance cytometry is a label-free technique for high-throughput single-cell analysis. Multi-frequency impedance measurements provide data that allows full characterisation of cells, linking electrical phenotype to individual biophysical properties. To efficiently extract the information embedded in the electrical signals, potentially in real-time, tailored signal processing is needed. Artificial intelligence approaches provide a promising new direction. Here we demonstrate the ability of neural networks to decipher impedance cytometry signals in two challenging scenarios: (i) to determine the intrinsic dielectric properties of single cells directly from raw impedance data streams, (ii) to capture single-cell signals that are hidden in the measured signals of coincident cells. The accuracy of the results and the high processing speed (fractions of ms per cell) demonstrate that neural networks can have an important role in impedance-based single-cell analysis.
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Affiliation(s)
- Federica Caselli
- Department of Civil Engineering and Computer Science, University of Rome Tor Vergata, Rome, Italy.
| | - Riccardo Reale
- Center for Life Nano Science@Sapienza, Italian Institute of Technology (IIT), Rome, Italy
| | - Adele De Ninno
- Italian National Research Council - Institute for Photonics and Nanotechnologies (CNR - IFN), Rome, Italy
| | - Daniel Spencer
- School of Electronics and Computing Science, and, Institute for Life Sciences, University of Southampton, Highfield, Southampton, UK
| | - Hywel Morgan
- School of Electronics and Computing Science, and, Institute for Life Sciences, University of Southampton, Highfield, Southampton, UK
| | - Paolo Bisegna
- Department of Civil Engineering and Computer Science, University of Rome Tor Vergata, Rome, Italy.
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20
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Tang T, Liu X, Yuan Y, Zhang T, Kiya R, Yang Y, Suzuki K, Tanaka Y, Li M, Hosokawa Y, Yalikun Y. Assessment of the electrical penetration of cell membranes using four-frequency impedance cytometry. MICROSYSTEMS & NANOENGINEERING 2022; 8:68. [PMID: 35757522 PMCID: PMC9226050 DOI: 10.1038/s41378-022-00405-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/09/2022] [Revised: 05/16/2022] [Accepted: 05/30/2022] [Indexed: 05/02/2023]
Abstract
The electrical penetration of the cell membrane is vital for determining the cell interior via impedance cytometry. Herein, we propose a method for determining the conductivity of the cell membrane through the tilting levels of impedance pulses. When electrical penetration occurs, a high-frequency current freely passes through the cell membrane; thus, the intracellular distribution can directly act on the high-frequency impedance pulses. Numerical simulation shows that an uneven intracellular component distribution can affect the tilting levels of impedance pulses, and the tilting levels start increasing when the cell membrane is electrically penetrated. Experimental evidence shows that higher detection frequencies (>7 MHz) lead to a wider distribution of the tilting levels of impedance pulses when measuring cell populations with four-frequency impedance cytometry. This finding allows us to determine that a detection frequency of 7 MHz is able to pass through the membrane of Euglena gracilis (E. gracilis) cells. Additionally, we provide a possible application of four-frequency impedance cytometry in the biomass monitoring of single E. gracilis cells. High-frequency impedance (≥7 MHz) can be applied to monitor these biomass changes, and low-frequency impedance (<7 MHz) can be applied to track the corresponding biovolume changes. Overall, this work demonstrates an easy determination method for the electrical penetration of the cell membrane, and the proposed platform is applicable for the multiparameter assessment of the cell state during cultivation.
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Affiliation(s)
- Tao Tang
- Division of Materials Science, Nara Institute of Science and Technology, 8916-5 Takayama-cho, Ikoma, Nara, 630-0192 Japan
| | - Xun Liu
- Division of Materials Science, Nara Institute of Science and Technology, 8916-5 Takayama-cho, Ikoma, Nara, 630-0192 Japan
| | - Yapeng Yuan
- Center for Biosystems Dynamics Research (BDR), RIKEN, 1-3 Yamadaoka, Suita, Osaka, 565-0871 Japan
| | - Tianlong Zhang
- Division of Materials Science, Nara Institute of Science and Technology, 8916-5 Takayama-cho, Ikoma, Nara, 630-0192 Japan
- School of Engineering, Macquarie University, Sydney, 2109 NSW Australia
| | - Ryota Kiya
- Division of Materials Science, Nara Institute of Science and Technology, 8916-5 Takayama-cho, Ikoma, Nara, 630-0192 Japan
| | - Yang Yang
- Institute of Deep-Sea Science and Engineering, Chinese Academy of Sciences, Sanya, Hainan 572000 P. R. China
| | | | - Yo Tanaka
- Center for Biosystems Dynamics Research (BDR), RIKEN, 1-3 Yamadaoka, Suita, Osaka, 565-0871 Japan
| | - Ming Li
- School of Engineering, Macquarie University, Sydney, 2109 NSW Australia
| | - Yoichiroh Hosokawa
- Division of Materials Science, Nara Institute of Science and Technology, 8916-5 Takayama-cho, Ikoma, Nara, 630-0192 Japan
| | - Yaxiaer Yalikun
- Division of Materials Science, Nara Institute of Science and Technology, 8916-5 Takayama-cho, Ikoma, Nara, 630-0192 Japan
- Center for Biosystems Dynamics Research (BDR), RIKEN, 1-3 Yamadaoka, Suita, Osaka, 565-0871 Japan
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